| Resumo: | In this paper we present a generalization and a computational improvement of the Bound Improvement Sequence Algorithm. The main computational burden of this algorithm consists in determining whether there exists a feasible point on the objective hyperplane, when the algorithm encounters a fixed point. By generalizing the algorithm, which consists in treating the objective function and the constraints alike, the number of fixed points for the objective hyperplane can be reduced, thus making the algorithm more efficient. We give computational results comparing the original algorithm with the proposed generalized algorithm, which shows that, loosely constrained problems, the number of fixed points generally be reduced.
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